Self-monitoring

Attention Escape
Teaching the learner to independently observe and record their own behaviour during a task or routine.

Self-monitoring as an antecedent strategy involves setting the learner up with a system to track their own behaviour before the session begins - a wristband counter, a simple tally sheet, a visual checklist - so that external adult monitoring becomes less necessary over time.

You use this when a learner is dependent on constant adult prompting to stay on task or follow a routine, and when that dependency is itself becoming the barrier to independence. The self-monitoring system becomes the antecedent cue that replaces the adult prompt.

For attention-maintained behaviour, self-monitoring removes the adult from the equation - the learner is getting attention from themselves rather than engineering it from you. For escape-maintained behaviour, a visual checklist of steps makes the task feel finite and controllable, reducing the motivation to escape something that feels endless.

The most common implementation error is skipping the teaching phase. Self-monitoring is a skill that requires explicit instruction, modelling, and practice before it works independently. Handing a learner a tally sheet and hoping for the best is not self-monitoring - it's wishful thinking. Another mistake is making the recording too complex. If the system requires more effort than the task itself, it won't be used.

Implementation

  1. Identify the specific behaviour the learner will monitor (e.g., on-task behaviour, steps completed).
  2. Select a simple recording method matched to the learner's skill level.
  3. Explicitly teach the learner how and when to record using modelling and rehearsal.
  4. Begin with high prompting and fade adult involvement gradually.
  5. Compare the learner's self-recorded data against your own to check accuracy and provide feedback.

Common Mistakes

  • Introducing self-monitoring without explicitly teaching the recording procedure first.
  • Using a recording system that is too complex or disruptive to the task itself.
  • Failing to verify accuracy by comparing against independent observer data.